治療効果の評価：RCTを実世界データで補完する

While randomized controlled trials remain the gold standard for assessing treatment efficacy, studies using real-world data (RWD) offer valuable insights into treatment effectiveness across broader, more diverse patient populations. This commentary explores the importance of using fit-for-purpose data and emphasizes the need for rigorous evaluation of RWD quality to support valid and actionable evidence generation.

The utility of RWD-based studies depends heavily on the fitness-for-purpose of the data source, which requires careful assessment of 5 key quality dimensions: relevance, extensiveness, timeliness, coherence, and reliability. Practical examples from coronavirus disease 2019 (COVID-19) comparative effectiveness research are used to illustrate each data quality domain.

As the need for RWD increases, especially for post-COVID-19 pandemic decision-making, ensuring high data quality and appropriate study design is critical. Proper evaluation of RWD sources enhances the credibility of findings and supports their use in meta-analyses, clinical guidelines, and healthcare policy.